Twenty five years after identification of the HIV virus, the AIDS epidemic continues with an estimated 33 million individuals currently infected worldwide and 2.5 million new infections each year. Research to prevent and treat HIV infection has grown increasing sophisticated and the analytic challenges have become correspondingly complex. In this application we outline plans for the development of statistical methods that will be directly applicable to current problems in the field of HIV/AIDS research. In particular, we propose to develop methods for the analysis of data from stepped wedge randomized trials, trials to prevent mother to child transmission of HIV, discordant partner studies, and trials or studies which utilize two-phase or other complex sampling designs. Since HIV infection is typically asymptomatic and the time of infection is bounded by two test dates, we continue work on methods for interval censored data and focus on issues related to competing risks and correlated interval censored data. Finally, as the search for an effective HIV vaccine presents ever greater challenges, we propose to develop novel statistical methods for analyzing data from studies of T-cell based vaccines as well as HIV antigen-antibody interactions.